Data can be presented and interpreted and re-interpreted and over interpreted. The details and parameters are often skimmed over and missed. The devil is in the detail. It helps to be cynical and nit picky. Pedanticism only exists as a concept for those who don't appreciate the details and subtleties therin. People so often simply see what they want to see and remain happy in their self imposed echo chamber.
My bottom line is that we have a personal responsibility to think for ourselves. To be as healthy as we can be - by ourselves and for our own self. Then the whole data thing is interesting when viewed as an outsider. I have come to realise that the data we are given is not just open to interpretation, it is massively open to fraud. We are presented all these figures and charts and numbers and statistics which we have to take at face value. But what of them are actually real or as they initially appear? Governments all over the world have stopped publishing and/or updating data. Data accumulated in sites such as ourworldindata take information as given by the governments. So - what is real, what is hidden, unknown, unassessed and misinterpreted?
Who knows. I don't. Even when I think I know I still keep questioning. The answers will either confirm or enlighten... So sad that so many people grow out of the 'why?' phase of life at such an early stage.
"But if this is generalizable, then it means that they also became infected at the highest rate just before the study begins, from mid-June to mid-September. Which means they are heavily represented in the BA.4/5 group, which experiences the least infections from mid-September to mid-December. Which also means, that in the next three months, the heavily-boosted who were infected during the study period will be the least infected."
I don't think so. Fall infection rates were about 2% in the no-dose group, 3.3% in the 1-dose group, 4.6% in the 2-dose group, 5.5% in the 3 dose group and 6% in the > 3 dose group. All are well under 10% and vary by at most a factor of 3. There were more infections in the summer. If we assume the ratios between groups didn't vary that tells us rates were about 3% in the no-dosers and 10% in the >3 dosers. Removing 10% of the >3 dosers from the eligibility pool (or even the probability of infection pool) due to recent infection still leaves 90% to get infected in the fall. It's a simple matter to see that the same stable infection rates could be maintained from season to season due to low-enough infection rates to minimize the number of recently infected and therefore more immune.
The same paper reports an bivalent booster efficacy of 30%. They are not at all clear about the reference point for the bivalent RR calculation. Using the already elevated rates for 2, 3 or 3+ doses is a great way to cheat. But let's just assume 30% to be generous. Is this relative to the That suggests a window of perhaps 60 to at most 120 days of some degree of vaccine efficacy in preventing at least a detected infection. This suggests that perhaps there was still summer efficacy for some of the >3 dosers who were vaccinated in the spring, but probably 1-3 months earlier relative to the risk window start date than the bivalent boosted were for the fall. So perhaps there is a bit of catch up, but I would argue most of this is higher infection rates in those with lots of doses, especially among those with no dose within about the past 90 days.
Over on twitter some Australian politician wondered if the mRNA shots are actually driving the production of variants because they probably have errors in their mRNA and they don't have perfect copy fidelity: https://twitter.com/SenatorRennick/status/1609884867839553537
At first I thought that must be rubbish, but then I got to wondering if someone who was boosted several times and has had their b-cells class switch to producing IgG4 antibodies it seems possible that in some cells they might be churning out virions that have Spike generated from defective mRNA ...
Of course, who knows how many of those defective Spike proteins would actually allow the virions to function of even if this is possible.
Dec 31, 2022·edited Dec 31, 2022Liked by Brian Mowrey
I'm late to this but this is a great description from a professor on infectious disease in S. Korea, admitting that a low level of natural immunity led to a sharp rise in Omicron, despite the third highest adult vaxx rate in the world at 97%
There's a fair degree of face saving in there but far more honesty than you'd get from mainstream health experts back here in the west.
Looks obvious in hindsight but the best protection from infection with Omicron is... infection from Omicron. All the mandates and unnecessary vaxxing only serve to keep the pandemic going.
It's interesting that cases in the UK are a small fraction of a few months ago but deaths are about the same; an inconvenient truth that must be ignored by the political and health leadership along with the media.
Anyway have the best New Year Brian and thanks for all your hard work! 🎆🎉🥳
Thanks for this trollish study challenge and the opportunity to tactilely participate in option selection! I appreciated the quiz was not too hard.
I am still wary of studies based on covid infections because of the unknown accuracy of PCR testing. This study tested for nucleic acid which in my understanding uses pcr. And it presumed that most people had symptoms before testing since the Cleveland clinic didn't require asymptomatic testing. I'm more confident in hospitalization and death data, and most confident in death data, even though that has been wonky too. I don't want to forget that infection data seems to be the least reliable.
"So all that the study is showing is that the highly-boosted are still catching up with natural immunity."
Maybe, Brian. I mean, while your interpretation fits the released data, the released data do not prove your interpretation. If you would just replace the first "is" with "may be" in the sentence above, I would have to agree (despite the siren song of groupthink).
However, what the study does NOT show is that continual boosting does anything whatsoever to prevent the spread of COVID on population level.
Other recent studies, and the overall prevalence of the illness, especially in highly vaccinated nations like Japan, present further evidence against continual boosting on population level.
I know from personal experience that getting COVID while unvaccinated sucks. But unlike those hiding in fear with 5+ mRNA doses who still got (or will get) COVID in the end anyway, I did my part for the greater "herd immunity" of my society.
I got it! the group that experienced the most infections was the group that experienced the most infections!
I haven't looked at this study, but noting that the large black line are those with no prior infection should raise some eyebrows as to how to interpret this information.
I suppose this is an example of the need for critical thinking, or really why it's so important that we teach people HOW to think more than WHAT. What would just tell us that the jabbed are getting infected the most, while HOW would tell us to take a careful look at how the information is stratified and what exactly the graph is measuring.
I'm actually curious of what you think of the whole IgG4 thing going on right now. I wrote a post but there's so much to discuss with it and I haven't formed all of my thoughts, but I looked at the supplemental data and there's some interesting information, including one person whose IgG4 ratio appeared to decline over time which...is weird? Not sure, this is all novel and we need more information.
I knew it. I KNEW it. Actually the original one made people more susceptible to the virus too. Barely anyone under 60 was getting sick prior to the vaccine, but afterward it seemed like everyone was.
Very interesting.
Data can be presented and interpreted and re-interpreted and over interpreted. The details and parameters are often skimmed over and missed. The devil is in the detail. It helps to be cynical and nit picky. Pedanticism only exists as a concept for those who don't appreciate the details and subtleties therin. People so often simply see what they want to see and remain happy in their self imposed echo chamber.
My bottom line is that we have a personal responsibility to think for ourselves. To be as healthy as we can be - by ourselves and for our own self. Then the whole data thing is interesting when viewed as an outsider. I have come to realise that the data we are given is not just open to interpretation, it is massively open to fraud. We are presented all these figures and charts and numbers and statistics which we have to take at face value. But what of them are actually real or as they initially appear? Governments all over the world have stopped publishing and/or updating data. Data accumulated in sites such as ourworldindata take information as given by the governments. So - what is real, what is hidden, unknown, unassessed and misinterpreted?
Who knows. I don't. Even when I think I know I still keep questioning. The answers will either confirm or enlighten... So sad that so many people grow out of the 'why?' phase of life at such an early stage.
Whoops, a bit of a ramble there.
Thanks for posting this Brian, it's good work.
"But if this is generalizable, then it means that they also became infected at the highest rate just before the study begins, from mid-June to mid-September. Which means they are heavily represented in the BA.4/5 group, which experiences the least infections from mid-September to mid-December. Which also means, that in the next three months, the heavily-boosted who were infected during the study period will be the least infected."
I don't think so. Fall infection rates were about 2% in the no-dose group, 3.3% in the 1-dose group, 4.6% in the 2-dose group, 5.5% in the 3 dose group and 6% in the > 3 dose group. All are well under 10% and vary by at most a factor of 3. There were more infections in the summer. If we assume the ratios between groups didn't vary that tells us rates were about 3% in the no-dosers and 10% in the >3 dosers. Removing 10% of the >3 dosers from the eligibility pool (or even the probability of infection pool) due to recent infection still leaves 90% to get infected in the fall. It's a simple matter to see that the same stable infection rates could be maintained from season to season due to low-enough infection rates to minimize the number of recently infected and therefore more immune.
The same paper reports an bivalent booster efficacy of 30%. They are not at all clear about the reference point for the bivalent RR calculation. Using the already elevated rates for 2, 3 or 3+ doses is a great way to cheat. But let's just assume 30% to be generous. Is this relative to the That suggests a window of perhaps 60 to at most 120 days of some degree of vaccine efficacy in preventing at least a detected infection. This suggests that perhaps there was still summer efficacy for some of the >3 dosers who were vaccinated in the spring, but probably 1-3 months earlier relative to the risk window start date than the bivalent boosted were for the fall. So perhaps there is a bit of catch up, but I would argue most of this is higher infection rates in those with lots of doses, especially among those with no dose within about the past 90 days.
duplicate - deleted
John Campbell discovers the Cleveland Clinic study. It is over.
Over on twitter some Australian politician wondered if the mRNA shots are actually driving the production of variants because they probably have errors in their mRNA and they don't have perfect copy fidelity: https://twitter.com/SenatorRennick/status/1609884867839553537
At first I thought that must be rubbish, but then I got to wondering if someone who was boosted several times and has had their b-cells class switch to producing IgG4 antibodies it seems possible that in some cells they might be churning out virions that have Spike generated from defective mRNA ...
Of course, who knows how many of those defective Spike proteins would actually allow the virions to function of even if this is possible.
I'm late to this but this is a great description from a professor on infectious disease in S. Korea, admitting that a low level of natural immunity led to a sharp rise in Omicron, despite the third highest adult vaxx rate in the world at 97%
https://youtu.be/fWTTSlSZC64?t=200
There's a fair degree of face saving in there but far more honesty than you'd get from mainstream health experts back here in the west.
Looks obvious in hindsight but the best protection from infection with Omicron is... infection from Omicron. All the mandates and unnecessary vaxxing only serve to keep the pandemic going.
It's interesting that cases in the UK are a small fraction of a few months ago but deaths are about the same; an inconvenient truth that must be ignored by the political and health leadership along with the media.
Anyway have the best New Year Brian and thanks for all your hard work! 🎆🎉🥳
Thanks for this trollish study challenge and the opportunity to tactilely participate in option selection! I appreciated the quiz was not too hard.
I am still wary of studies based on covid infections because of the unknown accuracy of PCR testing. This study tested for nucleic acid which in my understanding uses pcr. And it presumed that most people had symptoms before testing since the Cleveland clinic didn't require asymptomatic testing. I'm more confident in hospitalization and death data, and most confident in death data, even though that has been wonky too. I don't want to forget that infection data seems to be the least reliable.
🥂🥳 I wish you many blessings in the new year.
“A week ago (insanely; the holidays have certainly killed my productivity)...”
Holidays are SUPPOSED to kill your productivity. It’s a law! 😘
Thank you for all of your tireless work.
My father had covid immediately after the 4th dose.
My sister after the 3rd.
My colleague and her husband 3 days after the 2nd.
My neighbor died after the first dose.
No dose for me. Ever. My health is too important.
"So all that the study is showing is that the highly-boosted are still catching up with natural immunity."
Maybe, Brian. I mean, while your interpretation fits the released data, the released data do not prove your interpretation. If you would just replace the first "is" with "may be" in the sentence above, I would have to agree (despite the siren song of groupthink).
However, what the study does NOT show is that continual boosting does anything whatsoever to prevent the spread of COVID on population level.
Other recent studies, and the overall prevalence of the illness, especially in highly vaccinated nations like Japan, present further evidence against continual boosting on population level.
I know from personal experience that getting COVID while unvaccinated sucks. But unlike those hiding in fear with 5+ mRNA doses who still got (or will get) COVID in the end anyway, I did my part for the greater "herd immunity" of my society.
I got it! the group that experienced the most infections was the group that experienced the most infections!
I haven't looked at this study, but noting that the large black line are those with no prior infection should raise some eyebrows as to how to interpret this information.
I suppose this is an example of the need for critical thinking, or really why it's so important that we teach people HOW to think more than WHAT. What would just tell us that the jabbed are getting infected the most, while HOW would tell us to take a careful look at how the information is stratified and what exactly the graph is measuring.
I'm actually curious of what you think of the whole IgG4 thing going on right now. I wrote a post but there's so much to discuss with it and I haven't formed all of my thoughts, but I looked at the supplemental data and there's some interesting information, including one person whose IgG4 ratio appeared to decline over time which...is weird? Not sure, this is all novel and we need more information.
There's something weird going on with the number below the graph.
The first three rows are decreasing from left to right while the last two are increasing from left to right.
I guess I should read the paper to see what those numbers mean.
I knew it. I KNEW it. Actually the original one made people more susceptible to the virus too. Barely anyone under 60 was getting sick prior to the vaccine, but afterward it seemed like everyone was.